• DocumentCode
    604523
  • Title

    Reasoning research on vague information based on case-based reasoning and fuzzy-based reasoning in traditional Chinese medicine diagnosis

  • Author

    Feng Yang ; Hemin Jin ; Huimin Qi

  • Author_Institution
    Inst. of Inf. Technol., Henan Univ. of TCM, Zhengzhou, China
  • fYear
    2012
  • fDate
    29-31 Dec. 2012
  • Firstpage
    1813
  • Lastpage
    1817
  • Abstract
    There is a lot of vague information about TCM (Traditional Chinese Medicine) diagnosis difficult to understand through computer. Reasoning process, by coalescing of the CBR (Case-based Reasoning) and FBR (Fuzz-based Reasoning) in artificial intelligence, makes up for shortcomings of their alone, can achieve a good understanding of information in TCM diagnosis. As for the new diagnostic features, the reasoning algorithm firstly finds them in the existing case base, if fails, fuzzy reasoning mechanism will start automatically, then ultimately the credible results will be presented to the user. Facts have shown that the algorithm has good reasoning ability and can get more accurate diagnoses.
  • Keywords
    case-based reasoning; fuzzy reasoning; medical diagnostic computing; CBR; FBR; TCM diagnosis; artificial intelligence; case-based reasoning; fuzzy reasoning mechanism; fuzzy-based reasoning; reasoning ability; reasoning algorithm; traditional Chinese medicine diagnosis; vague information; CBR; FBR; Matching degree; Membership; TCM diagnosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4673-2963-7
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2012.6526271
  • Filename
    6526271